Detail
Článek
Článek online
FT
Medvik - BMČ
  • Je něco špatně v tomto záznamu ?

Modeling pre-spawning fitness and optimal climate of spotted snakehead Channa punctata (Bloch, 1793) from a Gangetic floodplain wetland of West Bengal, India

G. Karnatak, UK. Sarkar, M. Naskar, K. Roy, S. Nandi, P. Mishal, L. Lianthuamluaia, S. Kumari, BK. Das,

. 2020 ; 64 (11) : 1889-1898. [pub] 20200908

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc20027682

Grantová podpora
NICRA 2017-20 Indian Council of Agricultural Research (IN)

E-zdroje Online Plný text

NLK ProQuest Central od 2003-03-01 do Před 1 rokem
Medline Complete (EBSCOhost) od 2011-01-01 do Před 1 rokem
Health & Medicine (ProQuest) od 2003-03-01 do Před 1 rokem

The spawning and well-being of fish in an ecosystem are closely linked to climatic cues, viz., temperature and rainfall. Reduced fitness can affect the reproductive performance and lead to skipped spawning. Benchmarking the threshold fitness required for a fish population to achieve readiness for spawning, and understanding how climatic parameters influence the fitness will aid in predicting the fate of its reproductive success in future climatic conditions. This study determined the threshold condition factor pre-spawning fitness (Kspawn50) at which 50% of the female Channa punctata population can be deemed fit for spawning. The optimal climate within which pre-spawning fitness is attained by this species under Indian climatic conditions was also identified. The study was conducted from June 2015 to September 2016, covering two spawning seasons (June-August) in a Gangetic floodplain wetland of West Bengal, India. The non-parametric Kaplan-Meier method (survival fit) was used for estimation of pre-spawning fitness. "Ready to spawn" females were classified based on binary coding of the gonadal maturity stages. The thermal and precipitation range within which spawning fitness is achieved was identified by using the locally weighted smoothing technique. Female C. punctata pre-spawning fitness (Kspawn50) ranged from 1.26 to 1.39 with an estimated median of 1.29 units. Temperatures between 29 and 32 °C and rainfall above 100 mm were conducive to attaining the requisite pre-spawning fitness in C. punctata. This is the first study benchmarking the pre-spawning fitness and optimal climate for C. punctata. Understanding spawning requirements can inform the climate change-induced impacts on reproductive plasticity and evolutionary adaptations of snakeheads in the Ganga river basin.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc20027682
003      
CZ-PrNML
005      
20210114152225.0
007      
ta
008      
210105s2020 xxu f 000 0|eng||
009      
AR
024    7_
$a 10.1007/s00484-020-01976-z $2 doi
035    __
$a (PubMed)32897434
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxu
100    1_
$a Karnatak, Gunjan $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
245    10
$a Modeling pre-spawning fitness and optimal climate of spotted snakehead Channa punctata (Bloch, 1793) from a Gangetic floodplain wetland of West Bengal, India / $c G. Karnatak, UK. Sarkar, M. Naskar, K. Roy, S. Nandi, P. Mishal, L. Lianthuamluaia, S. Kumari, BK. Das,
520    9_
$a The spawning and well-being of fish in an ecosystem are closely linked to climatic cues, viz., temperature and rainfall. Reduced fitness can affect the reproductive performance and lead to skipped spawning. Benchmarking the threshold fitness required for a fish population to achieve readiness for spawning, and understanding how climatic parameters influence the fitness will aid in predicting the fate of its reproductive success in future climatic conditions. This study determined the threshold condition factor pre-spawning fitness (Kspawn50) at which 50% of the female Channa punctata population can be deemed fit for spawning. The optimal climate within which pre-spawning fitness is attained by this species under Indian climatic conditions was also identified. The study was conducted from June 2015 to September 2016, covering two spawning seasons (June-August) in a Gangetic floodplain wetland of West Bengal, India. The non-parametric Kaplan-Meier method (survival fit) was used for estimation of pre-spawning fitness. "Ready to spawn" females were classified based on binary coding of the gonadal maturity stages. The thermal and precipitation range within which spawning fitness is achieved was identified by using the locally weighted smoothing technique. Female C. punctata pre-spawning fitness (Kspawn50) ranged from 1.26 to 1.39 with an estimated median of 1.29 units. Temperatures between 29 and 32 °C and rainfall above 100 mm were conducive to attaining the requisite pre-spawning fitness in C. punctata. This is the first study benchmarking the pre-spawning fitness and optimal climate for C. punctata. Understanding spawning requirements can inform the climate change-induced impacts on reproductive plasticity and evolutionary adaptations of snakeheads in the Ganga river basin.
650    _2
$a zvířata $7 D000818
650    _2
$a klimatické změny $7 D057231
650    12
$a ekosystém $7 D017753
650    _2
$a ženské pohlaví $7 D005260
650    _2
$a rozmnožování $7 D012098
650    _2
$a řeky $7 D045483
650    12
$a mokřady $7 D053833
651    _2
$a Indie $7 D007194
655    _2
$a časopisecké články $7 D016428
700    1_
$a Sarkar, Uttam Kumar $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India. uksarkar1@gmail.com.
700    1_
$a Naskar, Malay $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
700    1_
$a Roy, Koushik $u Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Institute of Aquaculture and Protection of Waters, University of South Bohemiain České Budějovice, 370 05, České Budějovice, Czech Republic.
700    1_
$a Nandi, Saurav $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
700    1_
$a Mishal, Puthiyottil $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
700    1_
$a Lianthuamluaia, Lianthuamluaia $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
700    1_
$a Kumari, Suman $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
700    1_
$a Das, Basanta Kumar $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
773    0_
$w MED00002297 $t International journal of biometeorology $x 1432-1254 $g Roč. 64, č. 11 (2020), s. 1889-1898
856    41
$u https://pubmed.ncbi.nlm.nih.gov/32897434 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y a $z 0
990    __
$a 20210105 $b ABA008
991    __
$a 20210114152224 $b ABA008
999    __
$a ok $b bmc $g 1608017 $s 1118862
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2020 $b 64 $c 11 $d 1889-1898 $e 20200908 $i 1432-1254 $m International journal of biometeorology $n Int J Biometeorol $x MED00002297
GRA    __
$a NICRA 2017-20 $p Indian Council of Agricultural Research (IN)
LZP    __
$a Pubmed-20210105

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...